Data Scientist Manager

Ameriprise Financial is looking to add a Data Scientist Manager to the team! The individual in this role will play an integral role in supporting modeling and data analysis, campaign execution, and database needs for assigned line of business. Manage the creation and/or usage of large data sets, providing information-based decision logic and predictive modeling solutions, and translates modeling/analytic output into understandable/actionable business knowledge, insight and applications. Demonstrate strong technical/problem solving skills. Support multiple projects collaboratively.

Key Responsibilities

• Identify, develop and implement complex analytical solutions leveraging tools such as predictive modeling, advanced machine learning techniques, simulation, optimization solutions, etc., with respect to credit card, lending and cash products for marketing and risk management purposes.

• Manage dataset creation including data extraction, derived and dependent variable creation, and data quality control processes for analytics, model development, and validation. May monitor execution of analytical solutions, including criteria specification, data sourcing, segmentation, analytics, selection, delivery, and back-end data capture results.

• Consult and coordinate campaign execution for direct to client campaigns. Identify and execute targeting and optimization opportunities.

• Under direction of the Sr. Leader, collaborate with business leaders and/or analysts to provide analytical thought leadership and support for business problems. Identify and interpret business needs, define high-level business requirements, strategy, technical risks, and scope. Develop, document, and communicate business-driven analytic solutions and capabilities, translating modeling and analytic output into understandable and actionable business knowledge.

• Embed analytic programs and tools. Ensure continued accuracy, relevancy, and effectiveness and track process improvements once deployed.

• Ensure adherence to data and model governance standards that are set and enforced by industry standards and/or enterprise and business unit data governance polices and leaders.

• Contribute to ongoing expansion of data science expertise and credentials by keeping up with industry best practices, developing new skills, and knowledge sharing. Work cross functionally to develop standardized/automated solutions and adopt best practices.

Required Qualifications

• Masters degree or equivalent Quantitative Discipline (i.e. Finance, Statistics, Computer Science, Actuarial Science, Economics, Engineering, etc.)

• 3 - 5 years relevant experience required

• Knowledge of advanced statistical concepts and techniques; skilled in linear algebra.

• Experience conducting hands-on analytics projects using advanced statistical methods such as generalized regression models, Bayesian methods, random forest, gradient boosting, neural networks, machine learning, clustering, or similar methodologies.

• Experience with statistical programming (SAS, R, Python, SQL etc.) & data visualization software in a data-rich environment.

• Proven ability to present/communicate complex, technical materials in a way that facilitates decision making and drives outcomes; ability to communicate to less technical partners.

• Proven ability to apply both strategic and analytic techniques to provide business solutions and recommendations.

• Ability to work effectively in a collaborative team environment.

Preferred Qualifications

• Ph.D

• 3+ years of experience in statistical modeling and the collating processes necessary to create modeling data.

• Experience with big data technologies which may include Hadoop, Cloud Computing Environments (including container creation, management & deployment), Spark, Dataiku, Amazon SageMaker etc..

• Self-starter with the ability to work effectively in a matrix environment while (at times) working autonomously.

• Proven flexibility and adaptability in effectively driving results in an environment of changing priorities.

• Knowledge of credit risk analytics.

• Background in banking - lending, credit card and mortgage.

• Background in financial services.

We’re a diversified financial services leader with more than $1.5 trillion in assets under management, administration and advisement as of 2024. With our team of more than 20,000 people in 20 countries, we advise, manage and protect assets and income of more than 3.5 million individual, small business and institutional clients. We are a longstanding leader in financial planning and advice, a global asset manager and an insurer. Our unwavering focus on our clients and strong financial foundation connects each of our unique businesses - Ameriprise Financial, Columbia Threadneedle Investments and RiverSource Insurance and Annuities. Here, we foster meaningful careers, invest in the future, and make a difference for clients, institutions and communities around the world.